Motion planning for hybrid UAVs in dense urban environments

Abstract

Many hybrid UAVs capable of vertical takeoff and landing (VTOL) and fixed-wing flight are being introduced for their maneuverability, efficiency and high cruise speed. The benefits of these systems can be exploited effectively using task planning frameworks tailored to their unique properties. To address this need, we present a motion planning strategy for these hybrid UAVs in cluttered urban settings. After dividing the flight into three phases of takeoff, cruise and landing, we solve each of the ensuing motion planning problems using Stable Sparse RRT motion planner. We employ a Dubin's vehicle based model because it offers a balanced trade-off between computational simplicity and accurate simulation of real-world behavior. Simulation experiments conducted in a dense urban setting (downtown Chicago) show the efficacy of our approach.